I'm currentely trying to train a neural network that can decide wether a pattern produced by the movement of a hand near capacitive sensors is as expected, or random. I have an MPR121 microchip linked with an arduino, providing me 8 signals ( ranging from 0 to 255 ), that stays at baseline ( around 135 for my current conditions ) when nothing is near or perturbating the conductances. The value lowers when something conductive approaches it. Here is some pictures to help you represent the thing. The pattern of the eight channels together give information on the postion of the hand on one axis. The neural network is supposed to learn himself how the different channels react, in wich order, so i don't have to tell anything to the programm concerning the physical distance between two electrodes or whatever.
The fact is that i would like to learn how to do neural networks but i have no idea how to feed the data ( especially for data over time, which differs from typical image analysis tutorials often seen for neural networks over the internet ), considering that there is 100*8 values to analyse for each frame (100 values for 1 sec frame, for the eight channels ) and i don't know if i should have a network with 800 input nodes.... seems to me like i miss something...? Can i pass a list as one input to a neural network ,hence reducing the amount of input nodes to 8 ?
And another question i had, once trained, will th algorithm be exportable on an arduino ? I read somewhere that once trained, the weight of the nodes can be gathered, alowing to make an equation to choose from inputs to output, here yes or no. Arduino should be able to perform the calculation of this equation quite complex in a short amount of time i guess ?
( If you want to know, the labelisation of the data will be performed afterward, with a button connected to the arduino, telling him to record an d labellise as positive on an SD card the past 1 sec recording of the 8 channels. Everytime i will perform the hand pattern to be learnt, i will push this button. The randoms signals wich are labelled negative are 1 sec recordings, picked randomly over time of the day, to catch changes in baseline and hopefully some false positive noises due to people wandering around )
Thank you in advance for your help and advices on my project. =) And by the way, sorry for my english, hope i didn't shocked anyone.